Transform raw data from humanity's most powerful space telescope into publishable science with Python - the official JWST calibration pipeline that turns cosmic whispers into astronomical discoveries.

The James Webb Space Telescope captures the universe’s infrared secrets from its perch at the Earth-Sun L2 Lagrange point, but raw telescope data is like an uncut diamond - brilliant potential wrapped in instrumental noise, cosmic rays, and calibration artifacts. Every photon that traveled millions of years to reach JWST’s mirrors deserves the most sophisticated processing pipeline astronomers can build.

This official Python library from the Space Telescope Science Institute transforms those raw observations into publication-ready science products through a comprehensive calibration pipeline. It handles both imaging and spectroscopic data across all four JWST instruments, performing dark current subtraction, flat fielding, flux calibration, and dozens of other critical steps. Built on the robust AstroPy ecosystem, it processes everything from nearby exoplanet atmospheres to the most distant galaxies ever observed, with each calibration step traceable and customizable for specialized research needs.

Whether you’re hunting for biosignatures in TRAPPIST-1’s atmosphere or measuring the metallicity of galaxies at redshift 10, this pipeline has already processed the data behind JWST’s groundbreaking discoveries. Research institutions worldwide rely on these tools to extract every photon of scientific value from humanity’s $10 billion window into the infrared universe.

⭐ Stars: 634
💻 Language: Python
🔗 Repository: spacetelescope/jwst